Abstract

Abiotic variables, such as weather and tidal forces, are potentially as important as biotic factors (growth, predation, competition) in driving the variability of microphytobenthic (MPB) biomass on intertidal flats. Patterns of spatial distribution and temporal variability in MPB Chl. a, sediment Extracellular Polymeric Substances (EPS) and benthic diatom species composition were investigated during daily sampling spanning neap to spring tide periods on intertidal mudflats in the Colne Estuary, U.K., in three different seasons, with a particular focus on the influence of wind, rainfall, sun hours in the days prior to sampling, and tidal range. Spatial distribution (at < 1 m and <5 m scales) made the greatest contribution to biomass variability, followed by temporal (inter-monthly) variability. MPB Chl. a and EPS concentrations were positively correlated with sun-hours and tidal range, and negatively with rainfall and wind speed. Higher benthic MPB biomass was associated with lower suspended solid and Chl a loads, indicating biostabilisation of surface sediment. Suspended sediment loads and suspended Chl. a concentrations were positively correlated, and were significantly higher during neap rather than spring tides. Sediment settlement rates were higher during neap tides and related to suspended sediment load. The percent similarity in the benthic and suspended diatom assemblages (species relative abundance, RA) increased linearly with suspended solid load, with highest similarity during neap tides, with pennate benthic diatom taxa (Gyrosigma balticum, G. scalproides and Pleurosigma angulatum) dominant, indicating local sediment resuspension. During Spring tides, species similarity was lower, with a higher RA of planktonic centric diatoms (Actinoptychus, Coscinodiscus and Odontella) and lower sediment loads. Despite greater volumes of water movement during high tidal range periods, the highest levels of localised resuspension and remobilisation of MPB biomass across the mudflats occurred during low tidal range neap tide periods, when wind-induced waves were a key factor, particularly with shallower water depths over the intertidal mudflats.

Highlights

  • Microphytobenthos (MPB), the assemblages of autotrophic and het­ erotrophic algae, bacteria, fungi and protists and associated extracel­ lular biofilm matrices, occur widely in intertidal and shallow subtidal soft sediment habitats (Underwood and Kromkamp 1999)

  • In contrast to average sediment Chl. a, the average Extracellular Polymeric Substances (EPS) concentration was relatively higher on the mud flat compared to the transition zone sediments (Fig. 1B)

  • On the mud flat and the transition zone, ‘sum of sun hours’ increased Chl. a and EPS concentrations, and higher MPB biomass was associated with reduced MPB sediment-water column ex­ changes

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Summary

Introduction

Microphytobenthos (MPB), the assemblages of autotrophic and het­ erotrophic algae, bacteria, fungi and protists and associated extracel­ lular biofilm matrices, occur widely in intertidal and shallow subtidal soft sediment habitats (Underwood and Kromkamp 1999). Wind, temperature, nu­ trients and grazing are important drivers regulating the biomass and productivity of MPB (Blanchard et al, 2001; Orvain et al, 2004; Blanchard et al, 2006; Savelli et al, 2018; Rakotomalala et al, 2019) These drivers correlate with the spatial patterns of biomass, pro­ ductivity and species composition found across the intertidal gradient from upper to lower shore, and with different sediment particle sizes (Underwood 1994; Ribiero et al, 2013; Forster et al, 2006; Plante et al, 2016; Hill Spanik et al, 2019) and along estuarine salinity and nutrient gradients (Underwood and Paterson 1993; Forster et al, 2006; van der Wal et al, 2010). A key feature of MPB distribution is a high level of microspatial and micro-temporal variability in biomass (Spilmont et al, 2011; Weerman et al, 2011; Taylor et al, 2013; Daggers et al, 2020; Hope et al, 2020) underlying longer term seasonal and inter-annual patterns of variability (De Jonge et al, 2012; van der Wal et al, 2010; Benyoucef et al, 2014; Nedwell et al, 2016; Daggers et al, 2020)

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